Artificial Intelligence and Decision Support System to Determine Policies for Controlling River Pollution from Industrial Sectors

Abstract

One of the principal difficulties faced in developing countries is poor water quality. Approximately 90% households and industrial wastes are discharged untreated properly, directly into the ground and surface water. This research aims to analyze the use of artificial intelligence as a decision support system (DSS) to monitor and determine policies for controlling river pollution from industrial sectors. This study uses an interpretive approach or a qualitative approach by implementing the library research method. Integrated river basin management involves all management issues associated with the supply, use, rehabilitation, protection, pollution, and many others in a river basin. In the decision-making process, it considers the relations between the abiotic and the biotic part of the various water systems, between the ecological and economic factors, and between the various stakeholder interests. The use of technology by policymakers is important to address these water quality-related challenges. Therefore, DSS as an artificial intelligence tool is required to carry out river basin management processes. Thus, water managers can make policies and decisions on the implementation of measures to improve the quality of surface water in the river faster and more precise.